VNetPath: Diagnosis of Virtual Network Failures in Virtualized Environments through Path Tracing
Yinqin Zhao, Gaoxu Guo, Xingjian Zhang, Chang Liu, Long Wang, Yangyang Wang, Yefei Hou, Zhongwen Lan, Beibei Miao
Abstract
Virtualized environments are the foundation of modern computing, but their complex and dynamic virtual networks make failure diagnosis challenging. First, failures are often triggered by specific network flows, but generic probes cannot replicate these flows to reproduce and diagnose the fault. Second, existing diagnostic tools lack the required granularity, operating at the device or IP level and thus missing faults that occur at the level of network device ports (not the port concept in TCP or UDP). To fill the gap, we propose and implement VNetPath, an approach that directly diagnoses failures by replaying the network context of a failed request and constructing its end-to-end paths, operating at the granularity of network device ports with eBPF-based non-intrusive tracing. We conducted experiments by selecting typical network fault types from a real-world cloud system, designing fault injection methods, and injecting 6942 faults to a testbed cloud. Our experimental results show that VNetPath achieves a diagnosis accuracy of 93.45% on injected faults, demonstrating its ability to pinpoint failures that are invisible to telemetry systems like Zoonet (73.27%) and Traceroute (18.22%), while incurring a low standing overhead of only 0.81%.
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